Title
C-YES: An Efficient Parametric Yield Estimation Approach for Analog and Mixed-Signal Circuits Based on Multicorner-Multiperformance Correlations.
Abstract
Parametric yield estimation is a critical task for design and validation of analog and mixed-signal (AMS) circuits. However, the computational cost for yield estimation based on Monte Carlo (MC) analysis is often prohibitively high, especially when multiple circuit performances and/or environmental corners (e.g., voltage and temperature corners) are considered. In this paper, a novel statistical method named correlation-aided yield estimation (C-YES) is proposed to reduce the computational cost for parametric yield estimation. Our proposed approach exploits the fact that multiple circuit performances over different environmental corners are often correlated. Hence, we can accurately predict the performance value at one corner from the simulation results for other performances and/or corners. Based upon this observation, instead of running a large number of MC simulations to cover all performances and corners, an efficient algorithm is developed to select a small set of the most “informative” simulations that should be performed for yield estimation. Our numerical experiments show that for parametric yield estimation with multiple circuit performances and environmental corners, C-YES achieves 6.5– $9.3{ \\boldsymbol {\\times } }$ runtime speedups over other conventional methods.
Year
DOI
Venue
2017
10.1109/TCAD.2016.2613927
IEEE Trans. on CAD of Integrated Circuits and Systems
Keywords
Field
DocType
Integrated circuit modeling,Yield estimation,Correlation,Computational modeling,Analytical models,Circuit simulation,Computational efficiency
Monte Carlo method,And mixed signal,Computer science,Voltage,Electronic engineering,Parametric statistics,Electronic circuit,Small set
Journal
Volume
Issue
ISSN
36
6
0278-0070
Citations 
PageRank 
References 
2
0.39
15
Authors
6
Name
Order
Citations
PageRank
Wei Zeng111824.27
Hengliang Zhu28513.49
Xuan Zeng340875.96
Dian Zhou426056.14
Ruey-wen Liu523127.52
Xin Li653060.02